Advances in Genetics最新文献

Colorectal cancer (CRC) represents the second leading cause of cancer incidence and the third leading cause of cancer deaths worldwide. There is currently a lack of understanding of the onset of CRC, hindering the development of effective prevention strategies, early detection methods and the selection of appropriate therapies. This article outlines the key aspects of host genetics currently known about the origin and development of CRC. The organisation of the colonic crypts is described. It discusses how the transformation of a normal cell to a cancer cell occurs and how that malignant cell can populate an entire colonic crypt, promoting colorectal carcinogenesis. Current knowledge about the cell of origin of CRC is discussed, and the two morphological pathways that can give rise to CRC, the classical and alternative pathways, are presented. Due to the molecular heterogeneity of CRC, each of these pathways has been associated with different molecular mechanisms, including chromosomal and microsatellite genetic instability, as well as the CpG island methylator phenotype. Finally, different CRC classification systems are described based on genetic, epigenetic and transcriptomic alterations, allowing diagnosis and treatment personalisation.

Colorectal cancer (CRC) is the third leading cancer in incidence and the second leading cancer in mortality worldwide. There is growing scientific evidence to support the crucial role of the gut microbiota in the development of CRC. The gut microbiota is the complex community of microorganisms that inhabit the host gut in a symbiotic relationship. Diet plays a crucial role in modulating the risk of CRC, with a high intake of red and processed meat being a risk factor for the development of CRC. The production of metabolites derived from protein fermentation by the gut microbiota is considered a crucial element in the interaction between red and processed meat consumption and the development of CRC. This paper examines several metabolites derived from the bacterial fermentation of proteins associated with an increased risk of CRC. These metabolites include ammonia, polyamines, trimethylamine N-oxide (TMAO), N-nitroso compounds (NOC), hydrogen sulphide (H₂S), phenolic compounds (p-cresol) and indole compounds (indolimines). These compounds are depicted and reviewed for their association with CRC risk, possible mechanisms promoting carcinogenesis and their relationship with the gut microbiota. Additionally, this paper analyses the evidence related to the role of red and processed meat intake and CRC risk and the factors and pathways involved in bacterial proteolytic fermentation in the large intestine.

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related death worldwide. In recent years, the impact of the gut microbiota on the development of CRC has become clear. The gut microbiota is the community of microorganisms living in the gut symbiotic relationship with the host. These microorganisms contribute to the development of CRC through various mechanisms that are not yet fully understood. Increasing scientific evidence suggests that metabolites produced by the gut microbiota may influence CRC development by exerting protective and deleterious effects. This article reviews the metabolites produced by the gut microbiota, which are derived from the intake of complex carbohydrates, proteins, dairy products, and phytochemicals from plant foods and are associated with a reduced risk of CRC. These metabolites include short-chain fatty acids (SCFAs), indole and its derivatives, conjugated linoleic acid (CLA) and polyphenols. Each metabolite, its association with CRC risk, the possible mechanisms by which they exert anti-tumour functions and their relationship with the gut microbiota are described. In addition, other gut microbiota-derived metabolites that are gaining importance for their role as CRC suppressors are included.

Despite recent advancements in colorectal cancer (CRC) treatment, particularly with the introduction of immunotherapy and checkpoint inhibitors, the efficacy of these therapies remains limited to a subset of patients. To address this challenge, our study aimed to develop a prognostic biomarker based on immune-related genes to predict better outcomes in CRC patients and aid in treatment decision-making. We comprehensively analysed immune gene expression signatures associated with CRC prognosis to construct an immune meta-signature with prognostic potential. Utilising data from The Cancer Genome Atlas (TCGA), we employed Cox regression to identify immune-related genes with prognostic significance from multiple studies. Subsequently, we compared the expression levels of immune genes, levels of immune cell infiltration, and various immune-related molecules between high-risk and low-risk patient groups. Functional analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses provided insights into the biological pathways associated with the identified prognostic genes. Finally, we validated our findings using a separate CRC cohort from the Gene Expression Omnibus (GEO). Integration of the prognostic genes revealed significant disparities in survival outcomes. Differential expression analysis identified a set of immune-associated genes, which were further refined using LASSO penalisation and Cox regression. Univariate Cox regression analyses confirmed the autonomy of the gene signature as a prognostic indicator for CRC patient survival. Our risk prediction model effectively stratified CRC patients based on their prognosis, with the high-risk group showing enrichment in pro-oncogenic terms and pathways. Immune infiltration analysis revealed an augmented presence of certain immunosuppressive subsets in the high-risk group. Finally, we validated the performance of our prognostic model by applying the risk score equation to a different CRC patient dataset, confirming its prognostic potential in this new cohort. Overall, our study presents a novel immune-related gene signature with promising implications for predicting cancer progression and prognosis, thereby enabling more personalised management strategies for CRC patients.

Modern humans evolved in Africa some 200,000 years ago, and since then, human populations have expanded and diversified to occupy a broad range of habitats and use different subsistence modes. This has resulted in different adaptations, such as differential responses to diseases and different abilities to digest or tolerate certain foods. The shift from a subsistence strategy based on hunting and gathering during the Palaeolithic to a lifestyle based on the consumption of domesticated animals and plants in the Neolithic can be considered one of the most important dietary transitions of Homo sapiens. In this text, we review four examples of gene-culture coevolution: (i) the persistence of the enzyme lactase after weaning, which allows the digestion of milk in adulthood, related to the emergence of dairy farming during the Neolithic; (ii) the population differences in alcohol susceptibility, in particular the ethanol intolerance of Asian populations due to the increased accumulation of the toxic acetaldehyde, related to the spread of rice domestication; (iii) the maintenance of gluten intolerance (celiac disease) with the subsequent reduced fitness of its sufferers, related to the emergence of agriculture and (iv) the considerable variation in the biosynthetic pathway of long-chain polyunsaturated fatty acids in native populations with extreme diets.

This chapter overviews genetic techniques' fundamentals and methodological features, including different approaches, analyses, and applications that have contributed to advancing health and disease. The aim is to describe laboratory methodologies and analyses employed to understand the genetic landscape of different biological contexts, from conventional techniques to cutting-edge technologies. Besides describing detailed aspects of the polymerase chain reaction (PCR) and derived types as one of the principles for many novel techniques, we also discuss microarray analysis, next-generation sequencing, and genome editing technologies such as transcription activator-like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems. These techniques study several phenotypes, ranging from autoimmune disorders to viral diseases. The significance of integrating diverse genetic methodologies and tools to understand host genetics comprehensively and addressing the ethical, legal, and social implications (ELSI) associated with using genetic information is highlighted. Overall, the methods, procedures, and applications in host genetic analysis provided in this chapter furnish researchers and practitioners with a roadmap for navigating the dynamic landscape of host-genome interactions.

This chapter aims to explore the usefulness of the latest advances in genetic studies in the field of the circadian system in the future development of individualised strategies for health improvement based on lifestyle intervention. Due to the multifactorial and complex nature of the circadian system, we focus on the highly prevalent phenotypes in the population that are key to understanding its biology from an evolutionary perspective and that can be modulated by lifestyle. Therefore, we leave in the background those phenotypes that constitute infrequent pathologies or in which the current level of scientific evidence does not favour the implementation of practical approaches of this type. Therefore, from an evolutionary paradigm, this chapter addresses phenotypes such as morning chronotypes, evening chronotypes, extreme chronotypes, and other key concepts such as circadian rhythm amplitude, resilience to changes in circadian rhythm, and their relationships with pathologies associated with circadian rhythm imbalances.

This chapter analyses the interaction between microbiota and humans from an evolutionary point of view. Long-term interactions between gut microbiota and host have been generated as a result of dietary choices through coevolutionary processes, where mutuality of advantage is essential. Likewise, the characteristics of the intestinal environment have made it possible to describe different intrahost evolutionary mechanisms affecting microbiota. For its part, the intestinal microbiota has been of great importance in the evolution of mammals, allowing the diversification of dietary niches, phenotypic plasticity and the selection of host phenotypes. Although the origin of the human intestinal microbial community is still not known with certainty, mother-offspring transmission plays a key role, and it seems that transmissibility between individuals in adulthood also has important implications. Finally, it should be noted that certain aspects inherent to modern lifestyle, including refined diets, antibiotic intake, exposure to air pollutants, microplastics, and stress, could negatively affect the diversity and composition of our gut microbiota. This chapter aims to combine current knowledge to provide a comprehensive view of the interaction between microbiota and humans throughout evolution.

Colorectal cancer (CRC) is a heterogeneous disease with a complex aetiology influenced by a myriad of genetic and environmental factors. Despite advances in CRC research, it is a major burden of disease, with the second highest incidence and third leading cause of cancer deaths worldwide. To individualise diagnosis, prognosis, and treatment of CRC, developing new strategies combining precision medicine and bioinformatic procedures is promising. Precision medicine is based on omics technologies and aims to individualise the management of CRC based on patient host genetic characteristics and microbiota. Bioinformatics is central to the application of personalised medicine because it enables the analysis of large datasets generated by these technologies. At the level of host genetics, bioinformatics allows the identification of mutations, genes, molecular pathways, biomarkers and drugs relevant to colorectal carcinogenesis. At the microbiota level, bioinformatics is fundamental to analysing microbial communities' composition and functionality and developing biomarkers and personalised microbiota-based therapies. This paper explores the host and microbiota genetic data analysis in CRC research.

Acid-resistance in gastric pathogen Helicobacter pylori requires the coordination of four essential processes to regulate urease activity. Firstly, urease expression above a base level needs to be finely tuned at different ambient pH. Secondly, as nickel is needed to activate urease, nickel homeostasis needs to be maintained by proteins that import and export nickel ions, and sequester, store and release nickel when needed. Thirdly, urease accessary proteins that activate urease activity by nickel insertion need to be expressed. Finally, a reliable source of urea needs to be maintained by both intrinsic and extrinsic sources of urea. Two-component systems (arsRS and flgRS), as well as a nickel response regulator (NikR), sense the change in pH and act on a variety of genes to accomplish the function of acid resistance without causing cellular overalkalization and nickel toxicity. Nickel storage proteins also feature built-in switches to store nickel at neutral pH and release nickel at low pH. This review summarizes the current status of H. pylori research and highlights a number of hypotheses that need to be tested.